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    <title>Cufflinks RNA-Seq analysis tools - Getting Started</title>
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                <td> <a href="./index.html">
                    <h1>Cufflinks</h1>
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                  <h2>Transcript assembly, differential expression, and
                    differential regulation for RNA-Seq</h2>
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                    <a href="http://www.mcb.berkeley.edu/">
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                        border=0 src="images/UCBerkeley-seal.scaled.gif">
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                    <a href="http://genomics.jhu.edu/">
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                      src="images/JHU-seal.gif" border="0">
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          <h2>Site Map</h2>
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              <li><a href="index.html">Home</a></li>
              <li><a href="tutorial.html">Getting started</a></li>
              <li><a href="manual.html">Manual</a></li>
              <li><a href="howitworks.html">How Cufflinks works</a></li>
			  <li><a href="igenomes.html">Index and annotation downloads</a></li>
              <li><a href="faq.html">FAQ</a></li>
			  <li><a href="http://www.nature.com/nprot/journal/v7/n3/full/nprot.2012.016.html">Protocol</a></li>
			  <li><a href="report.html">Benchmarking</a></li>
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          <h2><u>News and updates</u></h2>
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                    <td>New releases and related tools will be announced
                      through the <a
                        href="https://lists.sourceforge.net/lists/listinfo/bowtie-bio-announce"><b>mailing
                          list</b></a></td>
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          <h2><u>Getting Help</u></h2>
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                    <td>Questions about Cufflinks and Cuffdiff should be posted on our <a href="https://groups.google.com/forum/#!forum/tuxedo-tools-users"><b>Google Group</b></a>. Please use <a
                        href="mailto:tophat.cufflinks@gmail.com">tophat.cufflinks@gmail.com</a> for private communications only.
                      Please do not email technical questions to
                      Cufflinks contributors directly.</td>
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            <h2><u>Releases</u></h2>
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                    <td>version 2.2.0</td>
                    <td align="right">5/25/2014</td>
                  </tr>
                  <tr>
                    <td><a href="./downloads/cufflinks-2.2.0.tar.gz"
                        onclick="javascript:
                        pageTracker._trackPageview('/downloads/cufflinks_source');
                        ">&nbsp;&nbsp;&nbsp;Source code</a></td>
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                    <td><a
                        href="./downloads/cufflinks-2.2.0.Linux_x86_64.tar.gz"
                        onclick="javascript:
                        pageTracker._trackPageview('/downloads/cufflinks');
                        ">&nbsp;&nbsp;&nbsp;Linux x86_64 binary</a></td>
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                    <td><a
                        href="./downloads/cufflinks-2.2.0.OSX_x86_64.tar.gz"
                        onclick="javascript:
                        pageTracker._trackPageview('/downloads/cufflinks');
                        ">&nbsp;&nbsp;&nbsp;Mac OS X x86_64 binary</a></td>
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          </div>     

		  <h2>Related Tools</h2>
          <div class="box">
            <ul>
                <li><a href="http://monocle-bio.sourceforge.net">Monocle</a>:
                  Single-cell RNA-Seq analysis</li>
				<li><a href="http://compbio.mit.edu/cummeRbund/">CummeRbund</a>:
	                Visualization of RNA-Seq differential analysis</li>
              <li><a href="http://tophat.cbcb.umd.edu/">TopHat</a>:
                Alignment of short RNA-Seq reads</li>
              <li><a href="http://bowtie.cbcb.umd.edu">Bowtie</a>:
                Ultrafast short read alignment</li>
            </ul>
          </div>


          <h2>Publications</h2>
          <div class="box">
            <ul>
              <li style="font-size: x-small; line-height: 130%">
                <p>Trapnell C, Williams BA, Pertea G, Mortazavi AM, Kwan
                  G, van Baren MJ, Salzberg SL, Wold B, Pachter L.<b> <a
                      href="http://dx.doi.org/10.1038/nbt.1621">Transcript
                      assembly and quantification by RNA-Seq reveals
                      unannotated transcripts and isoform switching
                      during cell differentiation</a></b> <br>
                  <i><a href="http://www.nature.com/nbt">Nature
                      Biotechnology</a></i> doi:10.1038/nbt.1621</p>
                <br>
              </li>
              <li style="font-size: x-small; line-height: 130%">
                <p>Roberts A, Trapnell C, Donaghey J, Rinn JL, Pachter
                  L.<b> <a
                      href="http://genomebiology.com/2011/12/3/R22/abstract">Improving
                      RNA-Seq expression estimates by correcting for
                      fragment bias</a></b> <br>
                  <i><a href="http://www.genomebiology.com">Genome
                      Biology</a></i> doi:10.1186/gb-2011-12-3-r22</p>
                <br>
              </li>
              <li style="font-size: x-small; line-height: 130%">
                <p>Roberts A, Pimentel H, Trapnell C, Pachter
                  L.<b> <a
                      href="http://bioinformatics.oxfordjournals.org/content/early/2011/06/21/bioinformatics.btr355.abstract">
                      Identification of novel transcripts in annotated genomes using RNA-Seq</a></b> <br>
                  <i><a href="http://bioinformatics.oxfordjournals.org/">Bioinformatics</a></i> doi:10.1093/bioinformatics/btr355</p>
                <br>
              </li>
			  <li style="font-size: x-small; line-height: 130%">
                <p>Trapnell C, Hendrickson D,Sauvageau S, Goff L, Rinn JL, Pachter L<b> <a
                      href="http://dx.doi.org/10.1038/nbt.2450">Differential 
					 analysis of gene regulation at transcript resolution with RNA-seq
					</a></b> <br>
                  <i><a href="http://www.nature.com/nbt">Nature
                      Biotechnology</a></i> doi:10.1038/nbt.2450</p>
                <br>
              </li>
            </ul>
          </div>
          <h2>Contributors</h2>
          <div class="box">
            <ul>
              <li><a href="http://www.cs.umd.edu/%7Ecole/">Cole Trapnell</a></li>
              <li><a href="http://www.cs.berkeley.edu/%7Eadarob/">Adam
                  Roberts</a></li>
              <li>Geo Pertea</li>
			  <li>David Hendrickson<li>
			  <li>Loyal Goff</li>
			  <li>Martin Sauvageau</li>
              <li>Brian Williams</li>
              <li><a href="http://wormlab.caltech.edu/members/">Ali
                  Mortazavi</a></li>
              <li>Gordon Kwan</li>
              <li>Jeltje van Baren</li>
			  <li><a href="http://www.rinnlab.com">John Rinn</a></li>
              <li><a href="http://www.cbcb.umd.edu/%7Esalzberg/">Steven
                  Salzberg</a></li>
              <li><a href="http://biology.caltech.edu/Members/Wold">Barbara
                  Wold</a></li>
              <li><a href="http://www.math.berkeley.edu/%7Elpachter/">Lior
                  Pachter</a></li>
            </ul>
          </div>
          <h2>Links</h2>
          <div class="box">
            <ul>
              <li><a href="http://bio.math.berkeley.edu/">Berkeley LMCB</a></li>
              <li><a href="http://www.cbcb.umd.edu/">UMD CBCB</a></li>
              <li><a href="http://woldlab.caltech.edu/">Wold Lab</a></li>
            </ul>
          </div>
        </div>
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        <div id="leftside">
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                <td>
                  <h1> Getting started</h1>
                  <br/>
                  <div id="toc">
                    <ul>
                      <li>Setting up Cufflinks</li>
                      <ul>
                        <li><a href="#inst">Install quick-start</a></li>
                        <li><a href="#ref">Test the installation</a></li>
                      </ul>
                      <li>Common uses of the Cufflinks package</li>
                      <ul>
                        <li><a href="#discovery">Discovering novel genes
                            and transcripts</a></li>
                        <li><a href="#differential">Identifying
                            differentially expressed and regulated genes</a></li>
                      </ul>
                    </ul>
                    <br/>
                  </div>
                  <br/>
                  <h2 id="inst">Install quick-start</h2>
                  <br/>
                  <strong>Installing a pre-compiled binary release</strong><br/>
                  <p>In order to make it easy to install Cufflinks, we
                    provide a few binary packages to save users from
                    occasionally frustrating process of building
                    Cufflinks, which requires that you install the Boost
                    libraries. To use the binary packages, simply
                    download the appropriate one for your machine, untar
                    it, and make sure the <tt>cufflinks</tt>,<tt>cuffdiff</tt>
                    and <tt>cuffcompare</tt> binaries are in a
                    directory in your PATH environment variable.</p>
                  <br/>
                  <strong>Building Cufflinks from source</strong><br/>
                  <p> In order to build Cufflinks, you must have the <a
                      href="http://www.boost.org">Boost C++ libraries</a>
                    (version 1.47 or higher) installed on your system.
                    See below for instructions on installing Boost. </p>
                  <br/>
                  <h3 id="boost">Installing Boost</h3>
                  <br/>
                  <ol>
                    <li><a href="http://www.boost.org/users/download/">Download</a>
                      Boost and the <tt>bjam</tt> build engine.</li>
                    <li>Unpack bjam and add it to your PATH.</li>
                    <li>Unpack the Boost tarball and <tt>cd</tt> to the
                      Boost source directory. This directory is called
                      the BOOST_ROOT in some Boost installation
                      instructions.</li>
                    <li>Build Boost. Note that you can specify where to
                      put Boost with the --prefix option. The default
                      Boost installation directory is <tt>/usr/local</tt>.
                      Take note of the boost installation directory,
                      because you will need to tell the Cufflinks
                      installer where to find Boost later on.
                      <p>If you are on Mac OS X, type (all on one line):
                        <br/>
                      </p>
                      <blockquote>bjam
                        --prefix=&lt;YOUR_BOOST_INSTALL_DIRECTORY&gt;
                        --toolset=darwin architecture=x86
                        address_model=32_64 link=static
                        runtime-link=static --layout=versioned stage
                        install</blockquote>
                    </li>
                    <p>If you are on a 32-bit Linux system, type (all on
                      one line): <br/>
                    </p>
                    <blockquote>bjam
                      --prefix=&lt;YOUR_BOOST_INSTALL_DIRECTORY&gt;
                      --toolset=gcc architecture=x86 address_model=32
                      link=static runtime-link=static stage install</blockquote>
                    <p>If you are on a 64-bit Linux system, type (all on
                      one line): <br/>
                    </p>
                    <blockquote>bjam
                      --prefix=&lt;YOUR_BOOST_INSTALL_DIRECTORY&gt;
                      --toolset=gcc architecture=x86 address_model=64
                      link=static runtime-link=static stage install</blockquote>
                  </ol>
                  <br/>
                  <h3 id="samtools">Installing the SAM tools</h3>
                  <br/>
                  <ol>
                    <li><a href="http://samtools.sourceforge.net/">Download</a>
                      the SAM tools</li>
                    <li>Unpack the SAM tools tarball and <tt>cd</tt> to
                      the SAM tools source directory.</li>
                    <li>Build the SAM tools by typing <tt>make</tt> at
                      the command line.</li>
                    <li>Choose a directory into which you wish to copy
                      the SAM tools binary, the included library <tt>libbam.a</tt>,
                      and the library headers. A common choice is <tt>/usr/local/</tt>.
                    </li>
                    <li>Copy libbam.a to the <tt>lib/</tt> directory in
                      the folder you've chosen above (e.g. <tt>/usr/local/lib/</tt>)</li>
                    <li>Create a directory called "<tt>bam</tt>" in the
                      <tt>include/</tt> directory (e.g.
                      /usr/local/include/bam) </li>
                    <li>Copy the headers (files ending in .h) to the <tt>include/bam</tt>
                      directory you've created above (e.g. <tt>/usr/local/include/bam</tt>)
                    </li>
                    <li>Copy the samtools binary to some directory in
                      your PATH.</li>
					</ol>
					<h3 id="samtools">Installing the Eigen libraries</h3>
	                  <br/>
	                  <ol>
						<li>Download <a href="http://eigen.tuxfamily.org/">Eigen</a></li>
						<li>Unpack the Eigen tarball and <tt>cd</tt> to
	                      the Eigen source directory.</li>
						<li>Copy the <tt>Eigen/</tt> subdirectory someplace on your system where you keep header files (e.g. <tt>/usr/local/include</tt>)
                  	  </ol>
                  <br/>
                  <h3 id="boost">Building Cufflinks</h3>
                  <br/>
                  <ol>
                    <li>Unpack the Cufflinks source tarball:
                      <blockquote>tar zxvf cufflinks-0.7.0.tar.gz</blockquote>
                    </li>
                    <li>Change to the Cufflinks directory:
                      <blockquote>cd cufflinks-0.7.0</blockquote>
                    </li>
                    <li>Configure Cufflinks. If Boost is installed
                      somewhere other than <tt>/usr/local</tt>, you
                      will need to tell the installer where to find it
                      using the <tt>--with-boost</tt> option. Specify
                      where to install Cufflinks using the <tt>--prefix</tt>
                      option.
                      <blockquote>./configure
                        --prefix=/path/to/cufflinks/install
                        --with-boost=/path/to/boost --with-eigen=/path/to/eigen</blockquote>
                      If you see any errors during configuration, verify
                      that you are using Boost version 1.47 or higher,
                      and that the directory you specified via <tt>--with-boost</tt>
                      contains the boost header files and libraries. See
                      the Boost <a href="">Getting started</a> page for
                      more details. If you copied the SAM tools binaries
                      to someplace other than <tt>/usr/local/</tt>, you
                      may need to supply the <tt>--with-bam</tt>
                      configuration option. </li>
                    <li>Finally, make and install Cufflinks.
                      <blockquote>make</blockquote>
                      <blockquote>make install</blockquote>
                    </li>
                  </ol>
                  <h2 id="test">Testing the installation</h2>
                  <br/>
                  <ol>
                    <li>Download the <a href="downloads/test_data.sam">test
                        data</a> </li>
                    <li>In the directory where you placed the test file,
                      type:<br/>
                      <blockquote>cufflinks ./test_data.sam</blockquote>
                      <br/>
                      You should see the following output:
                      <pre>[bam_header_read] EOF marker is absent. The input is probably truncated.
[bam_header_read] invalid BAM binary header (this is not a BAM file).
File ./test_data.sam doesn't appear to be a valid BAM file, trying SAM...
[13:23:15] Inspecting reads and determining fragment length distribution.
&gt; Processed 1 loci.                            [*************************] 100%
Warning: Using default Gaussian distribution due to insufficient paired-end reads in open ranges.  
It is recommended that correct paramaters (--frag-len-mean and --frag-len-std-dev) be provided.
&gt; Map Properties:
&gt;       Total Map Mass: 102.50
&gt;       Read Type: 75bp x 75bp
&gt;       Fragment Length Distribution: Truncated Gaussian (default)
&gt;                     Estimated Mean: 200
&gt;                  Estimated Std Dev: 80
[13:23:15] Assembling transcripts and estimating abundances.
&gt; Processed 1 loci.                            [*************************] 100%
</pre>
                    </li>
                    <li>Verify that the file <tt>transcripts.gtf</tt>
                      is in the current directory and looks like this
                      (your file will have GTF attributes, omitted here
                      for clarity)
                      <pre>test_chromosome Cufflinks       exon    53      250     1000    +       . 
test_chromosome Cufflinks       exon    351     400     1000    +       . 
test_chromosome Cufflinks       exon    501     550     1000    +       .
					
				</pre>
                    </li>
                  </ol>
                  <br/>
                  <h2>Common uses of the Cufflinks package</h2>
                  <br/>
				  <p>Cufflinks includes a number of tools for analyzing RNA-Seq experiments. Some of these tools can be run on their own, while others are pieces of a larger workflow. The complexity of your workflow depends on what you want to achieve with your analysis.  For a complete discussion of how Cufflinks can help you with your analysis, please see our protocol paper.  The paper includes a diagram (Figure 2) describing how the various parts of the Cufflinks package (and its companion tool TopHat) fit together.  As of version 2.2.0, you can also run Cuffquant and Cuffnorm to make large scale analyses easier to handle.  The figure below is an updated version of Figure 2 showing how the two utilities released after the protocol paper appeared fit into the workflow:
				  <img style="vertical-align:middle;padding-top:4px; display: block; margin-left: auto; margin-right: auto;"
				            border=0 src="images/tuxedo_workflow.png">
				 <p> You can use Cuffquant to pre-compute gene expression levels for each of your samples, which can save time if you have to re-run part of your analysis.  Using Cuffquant also makes it easier to spread the load of computation for lots of samples across multiple computers.  If you don't want to perform differential expression analysis, you can run Cuffnorm instead of Cuffdiff.  Cuffnorm produces simple tables of expression values that you can look at in R (for example) to cluster samples and perform other follow up analysis.</p>
				 <br/>
                  <h2 id="discovery">Discovering novel genes and
                    transcripts</h2>
                  <br/>
                  <p> RNA-Seq is a powerful technology for gene and
                    splice variant discovery. You can use Cufflinks to
                    help annotate a new genome or find new genes and
                    splice isoforms of known genes in even
                    well-annotated genomes. Annotating genomes is a
                    complex and difficult process, but we outline a
                    basic workflow that should get you started here. The
                    workflow also excludes examples of the commands
                    you'd run to implement each step in the workflow.
                    Suppose we have RNA-Seq reads from human liver,
                    brain, and heart. </p>
                  <p> <br/>
                  </p>
                  <ol>
                    <li><strong>Map the reads for each tissue to the
                        reference genome</strong></li>
                    <p> We recommend that you use TopHat to map your
                      reads to the reference genome. For this example,
                      we'll assume you have paired-end RNA-Seq data. You
                      can map reads as follows: </p>
                    <p> </p>
                    <blockquote> tophat -r 50 -o tophat_brain
                      /seqdata/indexes/hg19 brain_1.fq brain_2.fq 
                      tophat -r 50 -o tophat_liver /seqdata/indexes/hg19
                      liver_1.fq liver_2.fq 
                      tophat -r 50 -o tophat_heart /seqdata/indexes/hg19
                      heart_1.fq heart_2.fq 
                    </blockquote>
                    <p> The commands above are just examples of how to
                      map reads with TopHat. Please see the <a
                        href="http://tophat.cbcb.umd.edu/manual.html">TopHat


                        manual</a> for more details on RNA-Seq read
                      mapping. </p>
                    <br/>
                    <li><strong>Run Cufflinks on each mapping file</strong></li>
                    <p> The next step is to assemble each tissue sample
                      independently using Cufflinks. Assemble each
                      tissue like so: </p>
                    <blockquote> cufflinks -o cufflinks_brain
                      tophat_brain/accepted_hits.bam<br/>
                      cufflinks -o cufflinks_liver
                      tophat_liver/accepted_hits.bam<br/>
                      cufflinks -o cufflinks_heart
                      tophat_liver/accepted_hits.bam<br/>
                    </blockquote>
                    <li><strong>Merge the resulting assemblies</strong></li>
                    <tt><b>assemblies.txt:</b></tt>
                    <blockquote> cufflinks_brain/transcripts.gtf<br/>
                      cufflinks_liver/transcripts.gtf<br/>
                      cufflinks_heart/transcripts.gtf<br/>
                    </blockquote>
                    Now run the merge script:
                    <blockquote> cuffmerge -s
                      /seqdata/fastafiles/hg19/hg19.fa assemblies.txt<br/>
                    </blockquote>
                    <p>The final, merged annotation will be in the file
                      <tt>merged_asm/merged.gtf</tt>. At this point, you
                      can use your favorite browser to explore the
                      structure of your genes, or feed this file into
                      downstream informatic analyses, such as a search
                      for orthologs in other organisms. You can also
                      explore your samples with Cuffdiff and identify
                      genes that are significantly differentially
                      expressed between the three conditions. See the
                      workflows below for more details on how to do
                      this. </p>
                    <li><strong>(optional) Compare the merged assembly
                        with known or annotated genes</strong></li>
                    If you want to discover new genes in a genome that
                    has been annotated, you can use <tt>cuffcompare</tt>
                    to sort out what is new in your assembly from what
                    is already known. Run cuffcompare like this:
                    <blockquote> cuffcompare -s
                      /seqdata/fastafiles/hg19/hg19.fa -r
                      known_annotation.gtf merged_asm/merged.gtf<br>
                    </blockquote>
                    Cuffcompare will produce a number of output files
                    that you can parse to select novel genes and
                    isoforms.
                  </ol>
                  <br/>
                  <h2 id="differential">Identifying differentially
                    expressed and regulated genes</h2>
                  <br/>
                  <p> There are two workflows you can choose from when
                    looking for differentially expressed and regulated
                    genes using the Cufflinks package. The first
                    workflow is simpler and is a good choice when you
                    aren't looking for novel genes and transcripts. This
                    workflow requires that you not only have a reference
                    genome, but also a reference gene annotation in GFF
                    format (GFF3 or GTF2 formats are accepted, see
                    details <a href="gff.html">here</a>). The second
                    workflow, which includes steps to discover new genes
                    and new splice variants of known genes, is more
                    complex and requires more computing power. The
                    second workflow can use and augment a reference gene
                    annotation GFF if one is available. </p>
                  <br/>
                  <b>Differential analysis without gene and transcript
                    discovery</b>
                  <p> </p>
                  <ol>
                    <li><strong>Map the reads for each condition to the
                        reference genome</strong></li>
                    <p> We recommend that you use TopHat to map your
                      reads to the reference genome. For this example,
                      we'll assume you have paired-end RNA-Seq data.
                      Suppose you have RNA-Seq from a knockdown
                      experiment where you have two biological
                      replicates of a mock condition as a control and
                      two replicates of your knockdown. </p>
                    <p> <b>Note:</b> Cuffdiff will work much better if
                      you map your replicates independently, rather than
                      pooling the replicates from one condition into a
                      single set of reads. </p>
                    <p> </p>
                    <p> <b>Note:</b> While an GTF of known transcripts
                      is not strictly required at this stage, providing
                      one will improve alignment sensitivity, and
                      ultimately, the accuracy of Cuffdiff's analysis. </p>
                    <p> You can map reads as follows: </p>
                    <blockquote> tophat -r 50 -G annotation.gtf -o
                      tophat_mock_rep1 /seqdata/indexes/hg19 \<br/>
                      &nbsp;&nbsp;mock_rep1_1.fq mock_rep1_2.fq <br/>
                      tophat -r 50 -G annotation.gtf -o tophat_mock_rep2
                      /seqdata/indexes/hg19 \<br/>
                      &nbsp;&nbsp;mock_rep2_1.fq mock_rep2_2.fq <br/>
                      tophat -r 50 -G annotation.gtf -o
                      tophat_knockdown_rep1 /seqdata/indexes/hg19 \<br/>
                      &nbsp;&nbsp;knockdown_rep1_1.fq
                      knockdown_rep1_2.fq <br/>
                      tophat -r 50 -G annotation.gtf -o
                      tophat_knockdown_rep2 /seqdata/indexes/hg19 \<br>
                      &nbsp;&nbsp;knockdown_rep2_1.fq
                      knockdown_rep2_2.fq <br/>
                    </blockquote>
                    <li><strong>Run Cuffdiff</strong></li>
                    Take the annotated transcripts for your genome (as <a
                      href="gff.html">GFF or GTF</a>) and provide them
                    to <tt>cuffdiff</tt> along with the BAM files from
                    TopHat for each replicate:
                    <blockquote> cuffdiff annotation.gtf
                      mock_rep1.bam,mock_rep2.bam \<br>
                      &nbsp;&nbsp; knockdown_rep1.bam,knockdown_rep2.bam<br>
                    </blockquote>
                  </ol>
                  <br/>
                  <b>Differential analysis with gene and transcript
                    discovery</b>
                  <p> </p>
                  <ol>
                    <li><strong>Complete steps 1-3 in "Discovering novel
                        genes and transcripts", above</strong></li>
                    <p>Follow the protocol for gene and transcript
                      discovery listed above. Be sure to provide TopHat
                      and the assembly merging script with an reference
                      annotation if one is available for your organism,
                      to ensure the highest possible quality of
                      differential expression analysis. </p>
                    <li><strong>Run Cuffdiff</strong></li>
                    Take the merged assembly from produced in step 3 of
                    the discovery protocol and provide it to <tt>cuffdiff</tt>
                    along with the BAM files from TopHat:
                    <blockquote> cuffdiff merged_asm/merged.gtf
                      liver1.bam,liver2.bam brain1.bam,brain2.bam<br/>
                    </blockquote>
                    As shown above, replicate BAM files for each
                    conditions <strong>must</strong> be given as a
                    comma separated list. If you put spaces between
                    replicate files instead of commas, cuffdiff will
                    treat them as independent conditions.
                  </ol>
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                          <td> This research was supported in part by
                            NIH grants R01-LM06845 and R01-GM083873, NSF
                            grant CCF-0347992 and the Miller Institute
                            for Basic Research in Science at UC
                            Berkeley. </td>
                          <td align="right"> Administrator: <a
                              href="mailto:cole@cs.umd.edu">Cole
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